Based on the analysis of 190 studies (18,573 participants), we estimate that the average silent reading rate for adults in English is 238 words per minute (wpm) for non-fiction and 260 wpm for fiction. The difference can be predicted by taking into account the length of the words, with longer words in non-fiction than in fiction. The estimates are lower than the numbers often cited in scientific and popular writings. The reasons for the overestimates are reviewed. The average oral reading rate (based on 77 studies and 5,965 participants) is 183 wpm. Reading rates are lower for children, old adults, and readers with English as second language. The reading rates are in line with maximum listening speed and do not require the assumption of reading-specific language processing. Within each group/task there are reliable individual differences, which are not yet fully understood. For silent reading of English non-fiction most adults fall in the range of 175 to 300 wpm; for fiction the range is 200 to 320 wpm. Reading rates in other languages can be predicted reasonably well by taking into account the number of words these languages require to convey the same message as in English.
While it is recognized that language can pose a barrier to the transfer of scientific knowledge, the convergence on English as the global language of science may suggest that this problem has been resolved. However, our survey searching Google Scholar in 16 languages revealed that 35.6% of 75,513 scientific documents on biodiversity conservation published in 2014 were not in English. Ignoring such non-English knowledge can cause biases in our understanding of study systems. Furthermore, as publication in English has become prevalent, scientific knowledge is often unavailable in local languages. This hinders its use by field practitioners and policy makers for local environmental issues; 54% of protected area directors in Spain identified languages as a barrier. We urge scientific communities to make a more concerted effort to tackle this problem and propose potential approaches both for compiling non-English scientific knowledge effectively and for enhancing the multilingualization of new and existing knowledge available only in English for the users of such knowledge.
Gowtham Ramesh, Sumanth Doddapaneni, Aravinth Bheemaraj
et al.
We present Samanantar, the largest publicly available parallel corpora collection for Indic languages. The collection contains a total of 49.7 million sentence pairs between English and 11 Indic languages (from two language families). Specifically, we compile 12.4 million sentence pairs from existing, publicly available parallel corpora, and additionally mine 37.4 million sentence pairs from the Web, resulting in a 4× increase. We mine the parallel sentences from the Web by combining many corpora, tools, and methods: (a) Web-crawled monolingual corpora, (b) document OCR for extracting sentences from scanned documents, (c) multilingual representation models for aligning sentences, and (d) approximate nearest neighbor search for searching in a large collection of sentences. Human evaluation of samples from the newly mined corpora validate the high quality of the parallel sentences across 11 languages. Further, we extract 83.4 million sentence pairs between all 55 Indic language pairs from the English-centric parallel corpus using English as the pivot language. We trained multilingual NMT models spanning all these languages on Samanantar which outperform existing models and baselines on publicly available benchmarks, such as FLORES, establishing the utility of Samanantar. Our data and models are available publicly at Samanantar and we hope they will help advance research in NMT and multilingual NLP for Indic languages.
Existing multilingual machine translation approaches mainly focus on English-centric directions, while the non-English directions still lag behind. In this work, we aim to build a many-to-many translation system with an emphasis on the quality of non-English language directions. Our intuition is based on the hypothesis that a universal cross-language representation leads to better multilingual translation performance. To this end, we propose mRASP2, a training method to obtain a single unified multilingual translation model. mRASP2 is empowered by two techniques: a) a contrastive learning scheme to close the gap among representations of different languages, and b) data augmentation on both multiple parallel and monolingual data to further align token representations. For English-centric directions, mRASP2 achieves competitive or even better performance than a strong pre-trained model mBART on tens of WMT benchmarks. For non-English directions, mRASP2 achieves an improvement of average 10+ BLEU compared with the multilingual baseline
Ahmad Fitriansyah, Iwan Aprianto, Prasetyo Adi Nugroho
The Indonesian government through educational institutions has made various efforts to teach the language. Apart from Indonesian and regional languages, languages such as English, Arabic and Mandarin are some of the languages that will be taught to students. Arabic language learning at Madrasah Tsanawiyah Istiqlal Jakarta is going well, although there are still many students who have difficulty learning Arabic and tend to prefer English lessons. Some students find Arabic lessons difficult to understand. Easy and fun Arabic learning applications are needed to increase student interest. This research aims to produce a design for an interactive Arabic learning multimedia application. The method used is the Multimedia Development Life Cycle (MDLC) which consists of six phases, namely concept, design, material collection, production, testing and distribution. Use-case modeling is used to show application modeling where users can access several features provided by the application. The first testing stage uses the black box method by testing the application based on system responses such as the intro display, main page and buttons on the application. The second stage of beta testing consists of testing user acceptance of the application for Madrasah Tsanawiyah Istiqlal Jakarta students. Both stages of testing show that the application runs well and can be used correctly by users. User testing was carried out by calculating questionnaires from MTs Istiqlal Jakarta students which resulted in a score of 86.68%. This score shows that the usability aspect of Arabic language learning media is suitable for use.
The research examines the episode A Climate of Death from the British crime drama series Midsomer Murders (aired in December 2023), exploring how contemporary detective narratives integrate transcultural influences and ecological concerns. The study investigates the interplay of cultural diversity, environmental themes, and crime storytelling, using textual analysis as the primary method. Drawing on Wolfgang Welsch’s concept of transculturality alongside ecocritical and postmodern perspectives, the paper delves into the narrative strategies employed in this episode. By contrasting these elements with the more traditional frameworks of the Sherlock Holmes saga, the research highlights a shift in detective fiction – from reflecting Victorian-era cultural binaries to engaging with modern global anxieties. The study demonstrates that Midsomer Murders retains the genre’s foundational conventions while addressing contemporary societal challenges, creating a narrative space where local and global concerns converge.
Writing competence remains a critical yet challenging component of EFL teacher education, particularly in enabling pre-service teachers to design scaffolded, measurable, and genre-sensitive instructional objectives. Although the SMART framework (Specific, Measurable, Achievable, Relevant, and Time-bound) has been widely adopted in instructional planning, its systematic application and validation within writing pedagogy remain limited. Addressing this gap, the present study aimed to develop and validate a SMART-based instructional framework refined through the iterative Successive Approximation Model (SAM). Adopting a mixed-methods research and development (R&D) design, the study followed successive phases of preparation, design, development, implementation, and evaluation. The framework was validated by expert reviewers in language, material, and media, and subsequently trialed with fifth- and seventh-semester pre-service EFL teachers. Quantitative data were collected through validation instruments and competence assessments, while qualitative data were obtained from participant feedback, instructional artifacts, and reflective responses. Descriptive and inferential analyses indicated that the framework demonstrated strong content validity and instructional relevance, although aspects of practicality required further refinement. The iterative nature of SAM facilitated continuous improvement based on expert and user feedback, resulting in a more responsive and learner-centered design. The findings suggest that the SMART-based framework effectively enhances pre-service teachers’ competence in formulating instructional objectives for writing and functions as both a developmental and diagnostic tool in teacher education. This study contributes a praxis-oriented instructional framework that bridges theoretical rigor and classroom applicability, with implications for curriculum integration, genre-based scaffolding, and future development of technology-enhanced instructional supports.
This study explores the effectiveness of Mobile-Assisted Language Learning (MALL) in improving students’ English language skills in EFL (English as a Foreign Language) classrooms. Using a quantitative approach, data were collected through questionnaires involving 20 students and analyzed using statistical tests, including one-sample t-tests, Pearson correlations, and multiple linear regression. The results show that mobile applications significantly impact students' English language skills (r = 0.770, p < 0.01) and serve as a primary predictor of learning motivation (β = 0.744, p < 0.01). However, the average English language proficiency (mean = 29.8) and learning motivation through mobile applications (mean = 23.3) remain below the reference value (40).Interestingly, the impact of socioeconomic status on English proficiency and students' motivation was found to be insignificant (p > 0.05), indicating that equal access to technology can reduce social disparities in technology-based learning. This study underscores the significant potential of MALL in enhancing English skills, emphasizing the need for optimizing applications with interactive features and personalization. Recommendations include increasing the intensity of application use, training teachers in technology integration, and implementing inclusive policies to support students from diverse socioeconomic background.
The current study was undertaken to investigate how fresh graduates perform in English and why they were successful, reserved, or unsuccessful in job interviews from the perspective of the Systemic Functional Linguistics (SFL) Appraisal Theory namely from the Attitude subsystem. The theory focuses on the English language proficiency of the candidates in terms of their ability to express their stances in English. A qualitative method was employed in the present study. The data of the study comprised of walk-in interview transcripts of 10 fresh graduates for the post of Administrative Officer (s). An Appraisal analysis was conducted to reveal stances for the answers to the general interview question, “How do you face challenges?” and it was used as a theme to analyze the data. The findings revealed that the Appreciation subsystem of Attitude was used predominantly by candidates who were successful. The current study is expected to advance knowledge on the performance of graduates in job interviews and contribute to the field of SFL and Educational Linguistics.
History of scholarship and learning. The humanities, Social Sciences
This conversation on translation theory and practice with Michael Nieto Garcia and a mixed group of State University of New York (SUNY) students took place on 29 October 2019 at the Potsdam campus in New York State. The talk/interview was conducted by the invitation of Professor Richard M. Henry for his Literature and Translation Studies course (LITR520), and it was supported by the Dorf Yes fund at SUNY Potsdam. Some additions were made to the interview transcript to provide explanatory context and to articulate key points. A concluding thoughts section was added to summarize some translation takeaways.
When it comes to online reading activities, every student has a different motivation to read, particularly male and female students. The purpose of this study was to test the hypothesis (H1) saying that there is a significant difference between male and female students’ motivations in reading online. 31 male and 72 female students from ED of Sunville University, Indonesia are samples used in this quantitative study. To collect data, the researcher employed a questionnaire that was modified from Wigfield and Guthrie (1997). According to the data, male students’ reading motivation averages 2.58, while female students’ averages are 2.78 in using online platforms. The average score obtained from gender demonstrates a positive attitude. If the 2-tailed Sig. value is less than 0.05, a significant difference exists between male and female students’ reading motivations. This study has figures (.027) showing a significant difference between women and men in reading motivation. Thus, the H1 is accepted This suggests that the females and males have a different motivation level in reading online.